RESEARCH ARTICLE

Long-range hazard assessment of volcanic ash dispersalfor a Plinian eruptive scenario at Popocatépetl volcano(Mexico): implications for civil aviation safety

Rosanna Bonasia & Chiara Scaini & Lucia Capra &

Manuel Nathenson & Claus Siebe & Lilia Arana-Salinas &Arnau Folch

Received: 4 October 2013 /Accepted: 3 December 2013 /Published online: 15 December 2013# Springer-Verlag Berlin Heidelberg 2013

Abstract Popocatépetl is one of Mexico’s most activevolcanoes threatening a densely populated area that includesMexico City with more than 20 million inhabitants. Thedestructive potential of this volcano is demonstrated by itsLate Pleistocene–Holocene eruptive activity, which has beencharacterized by recurrent Plinian eruptions of large magni-tude, the last two of which destroyed human settlements inpre-Hispanic times. Popocatépetl’s reawakening in 1994 pro-duced a crisis that culminated with the evacuation of twovillages on the northeastern flank of the volcano. Shortly after,a monitoring system and a civil protection contingency planbased on a hazard zone map were implemented. The currentvolcanic hazards map considers the potential occurrence ofdifferent volcanic phenomena, including pyroclastic densitycurrents and lahars. However, no quantitative assessment ofthe tephra hazard, especially related to atmospheric dispersal,has been performed. The presence of airborne volcanic ash atlow and jet-cruise atmospheric levels compromises the safetyof aircraft operations and forces re-routing of aircraft to

prevent encounters with volcanic ash clouds. Given the highnumber of important airports in the surroundings of Popoca-tépetl volcano and considering the potential threat posed tocivil aviation in Mexico and adjacent regions in case of aPlinian eruption, a hazard assessment for tephra dispersal isrequired. In this work, we present the first probabilistic tephradispersal hazard assessment for Popocatépetl volcano. Wecompute probabilistic hazard maps for critical thresholds ofairborne ash concentrations at different flight levels, corre-sponding to the situation defined in Europe during 2010, andstill under discussion. Tephra dispersal mode is performedusing the FALL3D numerical model. Probabilistic hazardmaps are built for a Plinian eruptive scenario defined on thebasis of geological field data for the “Ochre Pumice” Plinianeruption (4965 14C yr BP). FALL3D model input eruptiveparameters are constrained through an inversion methodcarried out with the semi-analytical HAZMAP model andare varied by sampling them using probability density functions.We analyze the influence of seasonal variations on ash dispersaland estimate the average persistence of critical ash concentra-tions at relevant locations and airports. This study assesses theimpact that a Plinian eruption similar to the Ochre Pumiceeruption would have on the main airports of Mexicoand adjacent areas. The hazard maps presented here cansupport long-term planning that would help minimize theimpacts of such an eruption on civil aviation.

Keywords Popocatépetl . Tephra hazard . Plinian eruption .

Civil aviation . FALL3Dmodel

Introduction

Popocatépetl volcano is located in one of the most populatedareas of North America and considered one of the most active

Editorial responsibility: S. De la Cruz-Reyna

R. Bonasia (*) : L. CapraCentro de Geociencias, Universidad Nacional Autónoma deMéxico,Campus Juriquilla, 76230 Querétaro, Mexicoe-mail: rbonasia@geociencias.unam.mx

C. Scaini :A. FolchBarcelona Supercomputing Center-Centro Nacional deSupercomputación, Barcelona, Spain

M. NathensonU.S. Geological Survey, 345 Middlefield Road, Menlo Park,CA 94025, USA

C. Siebe : L. Arana-SalinasDepartamento de Vulcanología, Instituto de Geofísica, UniversidadNacionál Autónoma de México, 04510 Coyoacán, México, DF,Mexico

Bull Volcanol (2014) 76:789DOI 10.1007/s00445-013-0789-z

volcanoes in Mexico. Its past activity has been characterizedby catastrophic episodes including sector collapses andexplosive eruptions that emplaced pyroclastic density currentdeposits and dispersed tephra across east-central Mexico(Siebe and Macías 2006).

Popocatépetl became reactivated in 2004 and since thenhas displayed repeated episodes of dome growth thus farculminating in Vulcanian explosions producing short-livederuptive columns rising up to 8 km in height and triggeringsmall-volume pyroclastic density currents that spread outwarda few kilometers from the crater. In March 2012, after a periodof calm, the volcano entered into a new period of activity,characterized by an increase of seismic tremor and volcano-tectonic earthquakes, accompanied by ash columns that rose2–3 km in height (Martin-Del Pozzo 2012).

This new episode at Popocatépetl has to be assessed inview of a possible occurrence of a cataclysmic eruption.

Based on its Holocene eruptive record, Plinian eruptions atPopocatépetl occur with variable recurrence times of about1,000–3,000 years (Siebe et al. 1996). In particular, during theHolocene, three main short-lived Plinian eruptions have beenrecognized (Siebe et al. 1996; see also Table 1): (a) the UpperPre-Ceramic or Ochre Pumice eruption, that occurred at sometime between 3195 and 2830 year B.C. (Arana-Salinas et al.2010), (b) the Lower Ceramic or Lorenzo Pumice that oc-curred between 800 and 215 year B.C., and (c) the UpperCeramic or Pink Pumice eruption that occurred between 675and 1095 A.D. The stratigraphic evidence for these cases(Siebe et al. 1996; Arana-Salinas et al. 2010) indicates thatcataclysmic Plinian eruptive phases are typically preceded bysmall ash columns and phreato-magmatic explosions thatgenerate dilute pyroclastic density currents before the devel-opment of a sustained eruptive column with heights of around40 km and subsequent tephra dispersal towards the E-NE.

Despite the abundance of long-term geological data asso-ciated with Plinian scenarios at Popocatépetl, short-term pre-monitory signals diagnostic of an impending Plinian eruption(e.g., seismic patterns or SO2 degassing levels), are unclear.For this reason, it is of fundamental importance to assess thehazard posed by such an eruptive scenario in order to mitigatepossible catastrophic effects well ahead of time.

During the last 15 years, our knowledge of Plinian erup-tions that have occurred in Mexico and adjacent northernCentral America in the recent geologic past has increasedsignificantly and this information allows future scenarios tobe assessed from a much broader perspective. In addition toPopocatépetl, many other volcanoes in this region (Table 1and Fig. 1) have experienced Plinian eruptions during the LatePleistocene–Holocene. Although our list of Plinian eruptions(Table 1) is still fragmentary, it shows that in the past1,100 years, at least nine Plinian or sub-Plinian eruptions haveoccurred in the area. This number is much higher than previ-ously thought. In case of renewed Plinian activity at any of

these volcanoes, the effects would probably be analogous tothose caused by Popocatépetl with a large volume of tephradispersed over a similar sized area in the northern hemisphere.Hence, results of this study can also serve as a guide forassessing hazards at other volcanoes in this region with similarconditions.

The current hazard map for Popocatépetl volcano (Macíaset al. 1995) was produced quickly during the 1994–1995unrest and includes a hazard zonation scheme that considersdiverse phenomena including sector collapse, pyroclastic den-sity currents, lahars, and Plinian ash fallout. The tephra hazardzonation essentially consists of a circular area encompassingthe maximum observed extent of past fallout deposits. Thissimplistic tephra dispersal hazard representation certainlyneeds to be improved in order to produce a more detailedand comprehensive multi-hazard assessment at Popocatépetlvolcano.

Volcanic ash produced during explosive eruptions isamong the most hazardous volcanic phenomena. Apart fromthe direct impact of ash fallout, which can be responsible forroof collapses, disruption of terrestrial communications, anddamage to lifelines (Spence et al. 2005), airborne ash jeopar-dizes air travel safety (Casadevall 1993, 1994; Guffanti et al.2009; Miller and Casadevall 2000; Guffanti et al. 2010) andthreatens public health (Horwell and Baxter 2006). Thepresence of ash in the atmosphere in the vicinity of airportsreduces visibility and threatens the safety of aircraft duringlanding and take-off operations. Therefore, given the in-crease in frequency of flights and the number of passengersin Mexico and adjacent countries, assessing the impact ofvolcanic ash on civil aviation has become an importantissue.

In this work the Ochre Pumice eruption (OP, Arana-Salinaset al. 2010) was selected as a possible Plinian eruption sce-nario because it represents one of the best-studied Holoceneeruptions of this volcano and because, according to Mendoza-Rosas and De la Cruz-Reyna (2008), the probability of occur-rence of at least one eruption exceeding a VEI of 4 (i.e., amagnitude similar to that of the Ochre Pumice eruption), overa period of 100 years is 10 % and over 500 years is 43 %. Ourapproach follows the Eruption Range Scenario (ERS) pro-posed by Bonadonna et al. (2005) and Bonadonna (2006) andapplied by Biass and Bonadonna (2012) for the probabilistichazard assessment at Cotopaxi volcano in Ecuador. The ERSdescribes the probability of reaching a given tephra accumu-lation and dispersion based on the statistical distribution ofboth wind profiles and eruption source parameters.

Here we constrain eruptive parameters and characteristicsof the fallout deposit by means of the inversion methoddeveloped in Bonasia et al. (2010), which uses the HAZMAPmodel (Macedonio et al. 2005). The reconstructed parametersare varied by sampling them from probability density func-tions (PDF) and are used as input for the numerical code

789, Page 2 of 16 Bull Volcanol (2014) 76:789

Tab

le1

Physicalparametersof

know

nLatePleistocene–Holocenesub-Plinianto

Plin

ianeruptio

nson

Mexican

territo

ryandnorthern

CentralAmerica(inchronologicalo

rder)

Volcano

No.on

map

(Fig.1)

Lat

Lon

Altitude

(asl)

Eruption

Age

(yearBP)

Volum

e(D

RE)

Dispersal

direction

Colum

nheight

Com

positio

n(SiO

2in

wt.%

)VEI

Reference

ElC

hichón

117°21.5′

93°14′

1,100m

1982

A.D.1982

1.09

km3

NE-E

27–32km

565

Carey

andSigurdsson(1986);L

uhr

etal.(1984);Macíasetal.(2008);

Nathenson

andFierstein(2012)

Colim

a2

19°31′

103°37′

3,850m

1913

A.D.1913

0.30

km3

NE

23km

58–59

5Saucedo

etal.(2010);Saucedo

etal.

(2011)

SantaMaría

314°45.5′

91°33′

3,772m

1902

A.D.1902

2km

3NW

28km

65.7

6WilliamsandSelf(1983);R

oseetal.

(1977)

Cosigüina

412°59′

87°34.5′

872m

1853

A.D.1853

3–4km

3NNE

25–28km

57–60

5Scottetal.(2006);Selfetal.(1989)

Colim

a2

19°31′

103°37′

3,850m

1818

A.D.1818

––

–58–59

–Luhretal.(2010)

Colim

a2

19°31′

103°37′

3,850m

1576

A.D.1576

––

––

–Luhretal.(2010)

ElC

hichón

117°21.5′

93°14′

1,100m

CH550

550

1.1km

3NE

31km

55.3

4Macíasetal.(2003,2008)

Ceboruco

421°07′

104°30′

2,164m

JalaPum

ice

1.060

3–4km

3NE

25–30km

67–71

6GardnerandTait(2000);S

ieronand

Siebe

(2008)

Popocatépetl

619°01′

98°37.5′

5,452m

PinkPum

ice

1.100

2.5km

3NNE-E

–61–62

6Siebe

etal.(1996);Panfiletal.

(1999);S

chaafetal.(2005)

Ilopango

713°40′

89°03′

450m

TierraBlancaJoven

1.600(A

.D.536?)

39km

3NNW

orSE

?–

777

Dulletal.(2010)

Popocatépetl

619°01′

98°37.5′

5,452m

Lorenzo

Pumice

2.200

2km

3E

–61–62

6Siebe

etal.(1996);Panfiletal.

(1999);S

chaafetal.(2005)

Popocatépetl

619°01′

98°37.5′

5,452m

Ochre

Pumice

4.965

0.2km

3NNE

30–32km

61.5–63

4Thisstudy

TresVírgenes

827°28′

112°35.5′1,864m

LaVirgen

6.500

1.14

km3

SW18

km67.2–69.5

5Capra

etal.(1998)

Picode

Orizaba

919°02′

97°16′

5,675m

CitlaltépetlPum

ice

8.500–9.000

1.31

km3

SE23–28km

54–60

3Rossotti

etal.(2006)

Jocotitlán

1019°44′

99°45.5′

3,901m

Debrisavalanche

deposit

9.690

––

–64

4?Siebeetal.(1992)

Nevadode

Toluca

1119°07′

99°46′

4,680m

Upper

Toluca

Pumice

10.500

8km

3ENE

42km

63–66

6.25

Bloom

fieldetal.(1977);Arceetal.

(2003)

LaMalinche

1219°14′

98°02′

4,461m

MalinchePu

miceII

9.000–12.000

–NE

–59–60

–Castro-Govea

andSiebe(2007)

Nevadode

Toluca

1119°07′

99°46′

4,680m

MiddleTo

luca

Pumice

12.100

1.8km

3ESE-SE

18–20km

63.5–65

5.3

Arceetal.(2005)

Popocatépetl

619°01′

98°37.5′

5,452m

TuttiFrutiP

umice

14.100

3km

3NW

44km

616

Sosaetal.(2012)

SanJuan

1321°28′

104°58′

1,859m

TepicPu

mice

14.770

1.2km

3–

24km

67–70

5Luhr(2000)

Quetzalapa

1419°12′

97°22′

2,600m

QuetzalapaPu

mice

20.000

2.2km

3NNE

20km

715

Rodríguez-Elizarrarásetal.(2002)

LaMalinche

1219°14′

98°02′

4,461m

MalinchePum

iceI

21.470

––

–60–62

–Castro-Govea

andSiebe(2007)

Nevadode

Toluca

1119°07′

99°46′

4,680m

Low

erTo

luca

Pumice

21.700

0.8km

3NE

24km

61–65

5.3

Capra

etal.(2006)

Popocatépetl

619°01′

98°37.5′

5,452m

WhitePum

iceand

DAD

21–23.000

3.5km

3S

–59

6Siebe

etal.(1995);Schaafetal.

(2005)

Bull Volcanol (2014) 76:789 Page 3 of 16, 789

FALL3D (Costa et al. 2006; Folch et al. 2009) in order togenerate probability maps of ash dispersal in the atmosphere.

In the following section we provide a short description ofthe stratigraphy of the OP eruption. Then, we describe themethodology used to generate the probabilistic hazard maps,including the inversion strategy used to constrain the modelinput eruptive parameters. Finally, we present the results anddiscuss the implications for hazard assessment in terms ofimpact on civil aviation in the region.

Stratigraphy of the Ochre Pumice Plinian eruption

The Ochre Pumice eruption (Arana-Salinas et al. 2010) rep-resents Popocatépetl’s best-studied Holocene Plinian event.The composite stratigraphic section (Fig. 2) shows that theeruption sequence consists of: (1) A basal unit of pyroclasticsurge deposits with a total maximum thickness of 15 cm (sitePo-95185 of Fig. 2b in Arana-Salinas et al. 2010) at a distanceof 5 km from the vent, which can be recognized up to adistance of 13.5 km from the crater and is distributed on thenorth, north-east, and north-west volcano flanks; (2) the mainPlinian fallout deposit that consists of four units intercalatedby fine ash layers, interpreted as the result of column fluctu-ations, with a total maximum thickness of 250 cm at siteHuiloactlaxita (Po-95140 in Fig. 2b of Arana-Salinas et al.2010) at a distance of 6.3 km from the vent, and (3) an upperpyroclastic density current deposit sequence representing thefinal column collapse with a variable thickness ranging from80 to 40 cm and observable up to 5 km NE from the crater.The isopach map constructed by Arana-Salinas et al. (2010),shows a main dispersal axis oriented N-NE, from which theauthors calculated a total deposit volume of 4.9 km3 using themethod proposed by Pyle (1989, 1995) and Fierstein andNathenson (1992) with the model of Carey et al. (1995) forthe distal portion of the deposit. The maximum height of theeruptive column was constrained between 37 and 41 km withthe Carey and Sparks (1986) method, but our reanalysisindicates that column height was 31–32 km (see below). Themain components of this deposit are andesitic pumice(80 wt.%), accidental lithics (10 wt.%) from the conduit andthe local basement (granodiorite, limestones, and skarn), andglass shards and crystals of plagioclase and pyroxene(10 wt.%). The grain-size analyses indicate a poorly sorteddeposit, with a bimodal distribution enriched in the coarse ashfraction (0–2 ϕ) (Arana-Salinas et al. 2010).

Methodology

In order to generate the hazard maps we used the FALL3Dnumerical model (Costa et al. 2006; Folch et al. 2009), initial-ized with meteorological and volcanological parameters.T

able1

(contin

ued)

Volcano

No.on

map

(Fig.1)

Lat

Lon

Altitude

(asl)

Eruption

Age

(yearBP)

Volum

e(D

RE)

Dispersal

direction

Colum

nheight

Com

positio

n(SiO

2in

wt.%

)VEI

Reference

Tacaná

1515°56′

92°06.5′

4,063m

SibinalPu

mice

23.540

3km

3NNE

22km

48–61

4Arceetal.(2012b)

Jocotitlán

1019°44′

99°45.5′

3,901m

WhicteandGrey

Pumice

27.700

3.2km

3WSW

27– 30.7

km60–62.5

5Salin

asandSiebe(2007)

Guangoche

1619°43.5′

100°43′

2,770m

Póm

ezBlanca

29.030

0.5km

3E

21.6

km72–75

5Arceetal.(2012a)

Zitácuaro

1719°25′

100°14′

3,300m

LaDietaPu

mice

31.000

–Eor

NE

–65

5Capra

etal.(1997)

Tláloc

1819°24.5′

98°43′

4,150m

Multilayered

White

Pumice

31.000

1.58

km3

NE

24km

755

Rueda

etal.(2013)

Nevadode

Toluca

1119°07′

99°46′

4,680m

Ochre

Toluca

Pumice

36.000

––

––

–Bloom

fieldetal.(1977)

Notethatnotallparameterslistedwereobtained

with

thesamemethodologies

andarehencenotexactly

comparable

VEIvolcanicexplosivity

index,DREdenserock

equivalent,aslabovesealevel

789, Page 4 of 16 Bull Volcanol (2014) 76:789

FALL3D is a transient tephra dispersal model able to runacross different spatial scales, from local to regional. Weconsidered a computational domain spanning from 11° to37.5° N in latitude and from 74° to 110° W in longitude, withhorizontal grid resolution of 0.3° (∼30 km). The meteorolog-ical inputs were randomly sampled within a 6-year period(2001–2006) from the NCEP/DOE Reanalysis 2 dataset(Kalnay et al. 1996). The volcanological input parameters(known as eruption source parameters, ESP) required byFALL3D are column height, mass eruption rate (MER), ver-tical mass distribution, eruption duration, and the tephra totalgrain size distribution (TGSD). MER is estimated at eachnumerical iteration by FALL3D (Folch et al. 2009) and TGSDis assumed to be Gaussian with a constant dispersion. Thevertical distribution of mass in the eruption column wasassumed to follow a Suzuki distribution (Suzuki 1983;Pfeiffer et al. 2005) with parameters A=4 and λ =1, whichare typical of Plinian eruptions (Morton et al. 1956; Sparks1986). Column height, total erupted mass, and TGSD for thesimulated scenario were constrained bymeans of a best-fittingprocedure, described in the following section. For the gener-ation of probabilistic hazard maps we follow the eruptionrange scenario (Bonadonna et al. 2005; Bonadonna 2006).According to thismethodology, volcanological input parameterswere sampled from Gaussian probability density functions, asexplained in the following section.

Best-fit inversion method to constrain volcanological inputparameters

A best-fitting inversion was applied to reconstruct the OPdeposit data measured by Arana-Salinas et al. (2010) usingthe HAZMAP model (Macedonio et al. 2005).

One of the limitations of the model used derives from theparameterization of the eruptive column that is described as avertical line. This simplification is only valid where the as-cending column does not perturb the wind field, and the radiusof the eruption column can be neglected. Therefore the use ofthe model is limited to mid-distal sites (Macedonio et al.2005). For this reason we selected only 30 sections locatedat a distance greater than 10 km from the eruptive ventfrom the 150 stratigraphic sections measured by Arana-Salinas et al. (2010). Deposit thicknesses and grain-sizesmeasured by Arana-Salinas et al. (2010) and a depositdensity of 1,070 kg/m3 were used for converting thicknessto mass loading.

Given the limited number of the selected stratigraphicsections, the inversion procedure used is the one proposed inBonasia et al. (2010) that solves the inverse problem related tothe reconstruction of tephra fallout deposits of an eruption forwhich only few sampling data are available. The inversionprocedure consists of two steps: firstly we estimate the param-eters not directly dependent on granulometry (i.e., columnheight, column shape, wind profile, and diffusion coefficient)on a restricted range of granulometry classes having thebaricenter of the relative deposit distributions insidethe “convex hull” delimited by the sample sites; and secondly,we extended the inversion to all the other classes by fixing theparameters determined in the first step, allowing for the estima-tion of the bulk grain-size distribution and the total eruptedmass. The fitting was performed using the least-squares methodcomparing measured and calculated deposit thicknesses andgrain sizes (see Pfeiffer et al. 2005; Costa et al. 2009; Bonasiaet al. 2010 for further details).

Best-fit results are summarized in column 4 of Table 2, andFig. 3 shows the comparison between measured and best-fit

Fig. 1 Known Late Pleistocene–Holocene sub-Plinian eruptionson Mexican territory and innorthern central America. Lengthof arrow is proportional to thevolume (DRE) and hencemagnitude of a given eruption.Arrow direction indicates theplume–drift direction. Names ofvolcanoes (key in yellowtriangles , numbered inchronological order) are providedin Table 1. Column height andvolume (in parenthesis) of eacheruption are indicated next toeach arrow

Bull Volcanol (2014) 76:789 Page 5 of 16, 789

calculated mass loading for the 30 selected stratigraphicsections. Table 2 also shows median and sorting of thetotal grain size distribution reconstructed bymeans of the best-fit inversion method.

There is a significant difference in total mass and columnheight between values reported by Arana-Salinas et al. (2010)and the HAZMAP best-fit results (Table 2). Arana-Salinaset al. (2010) calculated volume by using the method proposedby Pyle (1989, 1995) and Fierstein and Nathenson (1992)based on the exponential reduction of the deposit thicknesscoupled with the model of Carey et al. (1995) for the distalportion of the deposit. The model of Carey et al. (1995)proposes that the thickness at the change in slope Tb is 0.12times the extrapolated thickness at zero area T0 and that thesecond slope k1 is between 0.010 and 0.015 km−1. Figure 4shows the data for thickness and areas from the isopachs inFigure 14A of Arana-Salinas et al. (2010) along with a single

straight-line approximation. The volume in this case is0.49 km3 (Table 2), in close agreement with the HAZMAPresults of 0.50 km3. The value of T0 is 264 cm, and for themodel of Carey et al. (1995), Tb is 32 cm. The second slopewas chosen as 0.013 km−1 in the mid-range of values pro-posed by Carey et al. (1995) and to yield a total volume of4.9 km3 as reported by Arana-Salinas et al. (2010). Figure 4shows the line obtained. The thickness at the change in slopeof 32 cm requires that both the areas of the 20 and 6 cmisopachs be much larger than found by Arana-Salinas et al.(2010), and this seems doubtful.

Reanalysis using the same methodology showed that theinitial calculation performed by Arana-Salinas et al. (2010) isin error because the area covered by the different isopachs wasdetermined wrongly.

A more recent model for estimating the thickness and thechange in slope at the slope of the second line is the systematicstudy of Sulpizio (2005). The area at the change in slope iscalculated from his equation (1) from the slope of the first line(0.104 km−1) as 861 km2. The second slope is calculated fromhis equation (6) as 0.023 km−1 and is shown in Fig. 4. Theestimate of the total volume is 1.21 km3. The ratio of proximalto total volume is 0.32, satisfying the inequality for his equa-tion (6). The change in slope is at thickness 12.6 cm, and thearea of the 6-cm isopach would have to be significantly largerthan that found by Arana-Salinas et al. (2010). The 6-cmisopach in Figure 14A of Arana-Salinas et al. (2010) is notdefined by many measured sections, and the larger area ispossible. The isomass contours from the HAZMAP calcula-tion have been converted to thickness, and the thickness andthe area are shown in Fig. 4. The HAZMAP calculations dohave a second slope (Fig. 4), but it is steeper than that foundusing the method of Sulpizio (2005). The estimates of volumebased on the isopachs and HAZMAP inversion agree well, butit is possible that the volume could be as large as 1.21 km3 asfound using the method of Sulpizio (2005).

The column heights reported by Arana-Salinas et al. (2010)of 37–41 km reference Carey and Sparks (1986). Applying thecalculations in Figure 7d for lithics of Carey and Sparks(1986) with interpolation, the buoyancy height Hb is 22 kmand the column height HT is 31 km (Table 2). From ourinversions, the value of column height is 32 km, similar tothe value from re-evaluating the isopleths data, and moreconsistent with an eruption of 0.49–1.21 km3. Carey et al.(1995) provide a correlation between column height and totalmass in their Figure 11, and the column height in this case forthe mass published by Arana-Salinas et al. (2010) is 26–34 km. Thus both methods give lower heights than whatwas reported. From the buoyancy and column heights of 22and 31 km, the mass eruption rate can be estimated fromFigure 6a in Sparks (1986) as 1.0×108 kg/s. The eruptionduration then goes from 4.5–9 h to 13.3 h. The mass eruptionrate estimated from the buoyancy and the column height of 22

Fig. 2 Composite stratigraphic section of the OP Plinian sequence thatsummarizes the eruptive history of the Ochre Pumice eruption, as de-scribed in Section “Stratigraphy of the Ochre Pumice Plinian eruption”(modified after Arana-Salinas et al. 2010)

789, Page 6 of 16 Bull Volcanol (2014) 76:789

and 31 km also applies to the total masses estimated using theisopachs and the method of Sulpizio (2005), and the eruptiontimes are 1.4 and 3.6 h, respectively (Table 2). Based on theisopleth map in Figure 14B of Arana-Salinas et al. (2010), thecrosswind range is 11.6 km and the downwind range is19.3 km for 1.5-cm lithics. These values can be used inFigure 16b of Carey and Sparks (1986) to estimate a column

top of 30 km, agreeing with the estimate above of 31 km. Theestimated wind speed is 16 m/s.

Fig. 4 Plot of thickness versus square root of area used to calculatevolumes. Data from Arana-Salinas et al. (2010; Fig. 14A) are shownalong with the line for calculating the volume with a single slope. Thedistal slopes are shown based on the method of Sulpizio (2005) and themethod of Carey et al. (1995) along with the thickness at change in slope.The areas for the isopachs for the HAZMAPmatching to the deposit datafor individual locations are shown along with the lines to calculate thevolume

Fig. 3 Log–log plot of the observed OP tephra deposit groundloads (kg/m2) versus the calculated tephra deposit ground loads (kg/m2)shows very good correlation

Table 2 Parameters for the OP tephra

This study Arana-Salinas et al. (2010) Notes

Isopachs Sulpizio (2005)method

HAZMAPinversion

As published Corrected

Tephra mass (kg) 5.2×1011 1.3×1012 5.3×1011 4.8×1012 (4.9/5.0) × total mass for Arana-Salinas et al. (2010)

Density (kg/m3) 0.9(900)+0.1(2,600)=1,070 984

Tephra volume (km3) 0.49 1.21 0.50 4.9

Area of 2.5-cm isopleth (km2) 370 Arana-Salinas et al. (2010; Fig. 14B)

Area of 1.5-cm isopleth (km2) 490 Arana-Salinas et al. (2010; Fig. 14B)

Buoyancy height HB (km) 22 Carey and Sparks (1986; Fig. 7d)

Column top HT (km) 31 32 Carey and Sparks (1986; Fig. 7d)

Column height HB−HT (km) 37–41 22–31 Carey and Sparks (1986; Fig. 7d)

Mass eruption rate (kg/s) 1.0×108 3.03×108 1.0×108 Sparks (1986; Fig. 6a)

Eruption time (h) 1.4 3.6 4.5–9 13.3

Crosswind range 1.5-cm isopleth (km) 11.6 Arana-Salinas et al. (2010; Fig. 14B)

Downwind range 1.5-cm isopleth (km) 19.3 Arana-Salinas et al. (2010; Fig. 14B)

Column top HT (km) 30 Carey and Sparks (1986; Fig. 16b)

Maximum wind speed (m/s) 16 Carey and Sparks (1986; Fig. 16b)

Total grain size distribution Mdϕ=4σϕ=2

Tephra volumes are calculated from areas of the isopachs using the method of Sulpizio (2005) and using the method of Carey et al. (1995) as reported byArana-Salinas et al. (2010). Values given for the HAZMAP match the deposit data for individual locations from a best-fit inversion. For column height,the values reported in Arana-Salinas et al. (2010; Table 6) could not be reproduced, and corrected values are given below. Figure number in notes reflectsthe figure in the citation used for the calculation

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These new eruption source parameters seem to representa reasonable data set, given the isopleths and isopachspublished in Arana-Salinas et al. (2010). According tothese data, the size and intensity of the OP eruption issignificantly lower, giving a VEI of 4, instead of 5. Accordingto Mendoza-Rosas and De la Cruz-Reyna (2008) such aneruption scenario has a greater likelihood of occurrence overa period of 100 or 500 years, being probabilities of 22 and77 %, respectively.

Since the eruptive scenario cannot be adequately definedusing single values for the volcanological inputs, it is neces-sary to define different eruptive range scenarios (Bonadonna2006) to account for their variability. Table 3 shows the rangesof input parameters used for the numerical simulation runs.According to the HAZMAP inversion method and the methodof Carey and Sparks (1986), our values of column heightrange between 22 and 32 km (Table 2). Here we adopt anaverage eruptive column of 30 km corresponding to results ofthe inversion with the method of Sulpizio (2005), while col-umn heights for the ERS range between 27.5 and 32.5 km. Forthe eruption duration, we consider the results obtained withthe Sulpizio (2005) method. Finally for the TGSD we take themedian of the particle grain-size distribution (4ϕ), result of theHAZMAP inversion, as a mean value and extended the grain-size distribution as shown in Table 3. Once a range for eacheruptive parameter was determined, we assumed a GaussianPDF between each range. The stratified sampling method(Krishnaiah and Rao 1988; Costa et al. 2009) is then used tosample volcanological input parameters for each run. Thismethod allows sampling a representative subset of the statis-tical population by extracting elements from each bin accord-ing to its relative probability (Scaini et al. 2012). Sampledvalues are generated by a random seed within each bin of theGaussian. For example, minimum, average, and maximumcolumn height are respectively 27,526, 30,003, and 32,385 m,sampled in the corresponding bins of the Gaussian PDF. Thus,the set of sampled eruptive source parameters is statisticallyrepresentative of the defined ERS.

While sampling, we estimated mass flow rate formaximum and minimum column height values and, giv-en the duration, we calculated ejected mass and volumethat correspond to the extreme values of our distributionvalues. We checked their consistency considering theVEI of the ERS, which, in this case, ranges between 4and 5.

Preparation of probabilistic hazard maps

In order to generate probabilistic hazard maps, we performed300 FALL3D runs with variable wind data and variableeruptive source parameters. Simulations were performed atthe Horus supercomputer (Computational GeodynamicsLaboratory, Querétaro, Mexico) using the parallel versionof the FALL3D code.

We built hazard maps for two particular flight levels (FL)that give the probability that airborne ash concentration ishigher than the critical value. As in past works on probabilistichazard assessment of tephra dispersal (Folch and Sulpizio2010; Scaini et al. 2012; Sulpizio et al. 2012), maps wereproduced at FL050 (altitude of 5,000 ft, ∼1.5 km) and FL300(altitude of 30,000 ft, ∼9.1 km), relevant for landing/take-offoperations and jet cruise altitude, respectively. Hazardmaps are produced for specific values of ash concentration,whose choice is still under development. After the 2010Eyafjallajökull eruption, much attention was focused on de-fining quantitative ash concentration thresholds for allowanceand airworthiness of civil aviation operations. Impacts of ashon aircraft engines have been known since the first encounterswith ash, in the 1980s (Casadevall 1993). Analysis of morethan 100 past encounters shows that ash can affect aircraftengines and components on both short- and long-term periods.Direct and indirect damages produce extremely high costs toairlines and are a big concern not only for flight safety but alsowith respect to maintenance of aircrafts. The InternationalVolcanic Ash Task Force (IVATF), established by theInternational Civil Aviation Organization (ICAO), identifiedthe choice of an ash concentration threshold as a criticalissue (IVATF-1 2010), whereas authorities at a national level,and in particular the Mexican National Centre for DisasterPrevention (CENAPRED), also declared their concern regard-ing the impact of explosive volcanic eruptions on air traffic(CENAPRED 2001). Currently in Europe, flight operationsare allowed at ash concentration lower than 2 mg/m3. During2010, a lower threshold value of 0.2 mg/m3 was also adoptedto define a restricted flying zone (IAVATF-1 2010). Recentdevelopments also suggest the adoption of specific thresholdsfor different engine types, and the definition of upper andlower ash concentration values, rather than a single threshold(EASA 2012). A comprehensive strategy for civil aviationmanagement during explosive eruptions is therefore still un-der consideration. Given that a strategy for airworthiness isstill not defined at international level, we decided to considerthe two concentration threshold values (2 and 0.2 mg/m3)adopted in 2010 during the European crisis, as both mightbe used for civil aviation management purposes.

In order to capture the effect of the seasonal variability onthe potential impact of ash on aerial navigation, seasonal mapsfor the same flight levels were also produced for the wetseason and the dry season.

Table 3 Input parameters used for the FALL3D numerical runs

Mean Minimum Maximum

Column height (m) 30,000 27,500 32,500

Eruption duration (h) 3.75 2.25 5.25

Mean grain size (ϕ) 4 2.25 5.25

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Finally, since a few millimeters of ash blanketing a largearea could cause airport disruption and the interruption ofcrucial communication networks, we constructed an ash load-ing probability map for the threshold of 1 kg/m2 that corre-sponds approximately to a deposit thickness of 0.1 cm.

Results

Figures 5 and 6 show hazard maps for the threshold values of2 and 0.2 mg/m3 at FL050 and FL300, respectively.

Figure 5a shows the map for FL050 and the 2 mg/m3

threshold. All probability contours are elongated toward theeast, and the 10 % probability contours exceed the computa-tional domain covering an area larger than 5 million km2.

According to these results the international airports of MexicoCity, Toluca, and Puebla have a very high probability (>80 %)of being affected by a concentration threshold greater than2 mg/m3, whereas some important tourist localities (e.g.,Mérida), lie within the 60 % probability area.

The FL050 for the 0.2 mg/m3 threshold (Fig. 5b)shows a probability distribution similar to that of the2 mg/m3, but the involved area is larger, since the 80 %probability curve reaches further also encompassing theairport of Ciudad del Carmen, which is of importance tothe oil industry. It is worth noting that the 60 % probabilitycurve is also more extended, reaching the international airportof Cuba.

The FL300 probability curves show the same trend foundfor the FL050 for both threshold values (Fig. 6a and b).

Fig. 5 Probabilistic hazard mapsat Flight Level FL050, for twoconcentration thresholds:a 2 mg/m3, b 0.2 mg/m3.Contours give probability, inpercent, of exceeding the giventhreshold value

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For both flight levels and ash concentration thresholds,results show that international airports in the southern USAcould also be affected. In particular, the Miami airportwould have a probability between 40 and 60 % ofexceeding both concentration thresholds at both flightlevels. The Houston international airport would have 20to 40 % probability of being affected by the consideredconcentration thresholds at FL50, and between 10 and20 % probability at FL300. Flights over the internationalairport of Dallas would have more than 5 % probabilityof being disrupted by an ash concentration threshold of 2and 0.2 mg/m3 at both flight levels. The internationalairport of Atlanta, lies within the moderate probabilityarea (>10 %) of the two considered ash-loading thresholds atboth flight levels.

In order to investigate the seasonal variability of ash dis-persal, we also constructed seasonal hazard maps (Folch andSulpizio 2010; Scaini et al. 2012) for the dry season (October–May) and the wet season (June–September), for both flightlevels but using the 2 mg/m3 threshold only (Figs. 7 and 8).For FL050, during the dry season (Fig. 7a), when windstypically blow eastward with higher intensity, the highestprobability contour (80 %) involves Mexico City, Puebla,and Veracruz, while the 60 % probability curve is moreelongated reaching Ciudad del Carmen and Cancún, andextends also towards the southeast of the volcano reachingthe city of Oaxaca. Almost the same probability distribution isevident during the wet season (Fig. 7b). During both seasons,the area covered by the low probability curve (5 %) iswidely extended and radially distributed around the volcano,

Fig. 6 Probabilistic hazard mapsat Flight Levels FL300, for twoconcentration thresholds: a2 mg/m3, b 0.2 mg/m3. Contoursgive probability, in percent, ofexceeding the given thresholdvalue

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potentially including an area of more than 6 million km2. Alow to moderate probability area (between 5 and 20 %) in-cludes the international airports of Puerto Vallarta (PacificMexican coast), Monterrey, and Houston, and embraces alsoDallas, Memphis, and Atlanta airports. For FL300 (Fig. 8aand b) a much more significant difference in the probabilitydistribution between the two seasons is noticed. During thedry season, the 80 and 60 % probability contours are moreextended than during the wet season. The higher probabilitycontour (80 %), during the dry season, is elongated towardsthe east and reaches Ciudad del Carmen, while during the wetseason it just affects the city of Veracruz. The 60% probabilitycontour reaches Cuba during the dry season, and only in-volves the cities of Ciudad del Carmen and Campeche duringthe wet season. During the dry season, lower to moderate

probabilities (between 5 and 40 %) affect some of the mostimportant airports in the south of USA, such as Dallas, Hous-ton, Memphis, and Atlanta. The airport of Miami has morethan 40 % probability of being affected by an ash concentra-tion greater than 2 mg/m3 at FL300. During the wet season,the same international airports fall in the lower probabilityarea (between 5 and 20 %) and the airport of Miami wouldhave less than 40 % probability of being affected by theconsidered concentration threshold.

Figure 9 shows the probabilities of exceeding a load thresh-old value of 1 kg/m2. The probability curves extend towardsthe east and embrace most of the principal airports of central-south Mexico. The Mérida international airport, for example,has between 10 and 20 % probability of being affected by anash loading greater than 1 kg/m2, a value that implies the

Fig. 7 Seasonal influence.Probabilistic hazard maps forFL050 for a concentrationthreshold of 2 mg/m3 during thedry (a) and wet season (b).Contours give probability, inpercent, of exceeding the giventhreshold value

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disruption of airport operations. The airports of Mexico City,Puebla, and Veracruz lie within the moderate to high proba-bility area (between 40 and 80 %).

Finally, we also computed the averaged ash residencetimes at FL300, for most relevant airports having a lowto high probability of exceeding the threshold of 2 mg/m3

(Table 4).

Summary and discussion

We constructed ash dispersion hazard maps for a modelPlinian eruption at Popocatépetl volcano using the FALL3Dtephra dispersal model. Volcanological model input parame-ters for this scenario were constrained by means of a best-

fitting between measured and calculated deposit thicknessesand grain-sizes, and were varied according to a samplingprocedure within probability density functions.

The best-fit erupted volume (0.50 km3) coincides with thevolume estimated using the single straight-line approximation(Pyle 1989) and represents the proximal deposit only since itis based on measured stratigraphic sections. The total eruptedvolume was also calculated by means of the Sulpizio (2005)method that gave a value of 1.21 km3.

The best-fit column height of 32 km is compatible with atotal erupted volume of 0.50–1.21 km3 and the re-evaluatedcolumn height of 31 km. Our best-fit values for total mass,column height, and TGSD were varied within PDFs andfurnished as inputs for the FALL3D model to construct prob-ability hazard maps of ash concentration for two threshold

Fig. 8 Seasonal influence.Probabilistic hazard maps forFL300 for a concentrationthreshold of 2 mg/m3 during thedry (a) and wet season (b).Contours give probability, inpercent, of exceeding the giventhreshold value

789, Page 12 of 16 Bull Volcanol (2014) 76:789

values of 2 and 0.2 mg/m3 and at two different flight levels(FL050, representative of landing/take-off operations, andFL300, representative of jet cruise altitude).

In order to take into account the effect of the seasonalvariability we also constructed hazard maps for the dry andwet seasons.

Expected impacts of ash dispersal in the atmosphere at theconsidered FLs are discussed below.

FL050

Figure 5a and b show that, in case of a future Plinian eruptionat Popocatépetl volcano, almost all airports in Mexico wouldhave a medium to high probability of being disrupted. The2 mg/m3 no-fly condition has a very high probability ofoccurring at the airports ofMexico City, Puebla, and Veracruz,three international airports that exceed 27 million passengersper year (statistics of Grupo Aeroportuario de la Ciudad deMéxico, http:/ /www.aicm.com.mx/acercadelaicm/Estadisticas/, and Aeropuertos y servicios auxiliares, http://www.asa.gob.mx/).

A probability larger than 60 % is found also for otherinternational airports such as Oaxaca, Mérida, and Cancún.Cancún has become a major tourist destination with more than14 million passengers in 2012. Considering the 10–60 %probability area (Fig. 5a and b), the number of airports thatwould be affected increases considerably, involving, amongothers, the international airport of Guadalajara with more than7 million passengers per year. Also the cities of Manzanillo(the most important Mexican harbor in the Pacific coast) andQuerétaro (capital of one of the most industrialized states ofthe country) are included in the same area, each one having aninternational airport, through which more than 280,000 peoplepass each year. Impact produced at southern USA airports isalso substantial. It is worth noting that the Miami internationalairport, the primary airport serving South Florida (USA) thatcounts with almost 40 million passengers every year, has aprobability greater than 40% of being disrupted. The Houstoninternational airport (Texas, USA) that serves the fifth-largestmetropolitan area in the United States, with more than 40millionpassengers in 2012, has between 10 and 20 % probability ofbeing affected by the considered critical ash-concentration

Table 4 Averaged residence times in hours at flight level FL300 for theconcentration threshold 2 mg/m3 (no-fly zone), at the Mexican andUnited States airports that have low to high probability of exceeding thegiven threshold

Airports Averageresidencetime (h)

Probability Number ofpassengersper year

Acapulco 52 30 546,951

Atlanta (US) 26 25 89,331,622

Cancun 25 68 14,463,435

Ciudad del Carmen 26 85 516,205

Colima 28 25 168,000

Dallas (US) 31 9 56,906,610

Guadalajara 26 20 7,436,400

Houston (US) 38 12 40,187,442

La Havana (Cuba) 25 60 >4,000,000

Memphis (US) 28 12 7,874,888

Mexico City 25 73 29,491,553

Miami (US) 21 50 39,500,000

Monterrey 31 12 6,105,910

Oaxaca 33 74 473,133

Puebla 23 100 264,211

Queretaro 33 28 226,908

Toluca 40 37 972,414

Veracruz 25 97 894,552

Number of passengers per year and probabilities of exceeding the giventhreshold are also reported

Fig. 9 Ash loading probabilitymap for the threshold value1 kg/m2. Contours giveprobability, in percent, ofexceeding the given thresholdvalue

Bull Volcanol (2014) 76:789 Page 13 of 16, 789

thresholds. Finally, it is worth mentioning that the internationalairport of Cuba that counts with more than 3 million aircraftoperations each year has more than 40 % probability of beingdisrupted.

FL300

Mexican air space may be strongly affected by the occurrenceof a Popocatépetl eruption like that modeled. In particular, theaerial corridors of central-south Mexico have a high probabil-ity of being disrupted, whereas aerial corridors passing overthe north of the country would be less likely affected, with aprobability of about 5 % (Fig. 6a and b).

Figure 6b shows that the majority of the airports in north-central Mexico would have low to moderate probability ofbeing affected by an ash concentration threshold of0.2 mg/m3, whereas the airports of Mexico City, Puebla, andCiudad del Carmen would havemore than 80% probability ofexceeding this concentration threshold. An ash concentrationvalue of 0.2 mg/m3 could lead to re-routing and other opera-tions to enhance air traffic security. For this reason, aerialcorridors, especially those passing over south-central Mexicowould have a high probability of being disrupted or eveninterrupted, with strong socio-economic consequences at na-tional and regional scale. As discussed for FL050, also in thiscase, the international airports of Houston (Texas, USA),Miami (Florida, USA), and Atlanta (Georgia, USA) wouldhave a low to moderate probability of exceeding the givenconcentration thresholds. In addition, also the internationalairport of Dallas (Texas, USA), which serves more than 50million passengers each year, is included in the area of 5 to10 % probability of being affected by a concentration thresh-old of 0.2 mg/m3 at the FL300. The area embraced by prob-ability curves during the dry season (Fig. 8a) is more extendedthan during the wet season.

Besides the impact of airborne ash on critical flight levels,the accumulation of few millimeters of ash could also threatenairport operations. Figure 9 shows that a wide area, east of thevolcano, would be affected by a low to high probability ofexceeding a loading threshold of 1 kg/m2. The tourist airportsof Mérida and Campeche, on the Yucatán peninsula, have 10to 20% probability of being disrupted by deposition of 0.1 cmof ash, while Mexico City, Puebla, and Veracruz have a muchhigher probability (>40 %).

Residence time is an important variable for civil aviationmanagement during a volcanic crisis and allows estimatingthe average duration of airport disruption, and consequentlythe impact in terms of the number of routes and passengersaffected (Sulpizio et al. 2012).

In case of a Plinian eruption lasting between 1 and4 h, ash residence times (Table 4) at the airports ofMexico City,Puebla, and Toluca would be 25, 23, and 40 h, respectively,causing serious disruption. Moreover, the airports of important

tourist destinations, such as Cancún and Ciudad del Carmen,would be affected by an ash residence time of 25 and 26 h,respectively. Beyond the area with a high probability of ex-ceeding the threshold of 2 mg/m3, the ash residence time overairports would still be high. Above the Querétaro airport anash concentration of 2 mg/m3 would persist for 33 h, whileover Colima and Acapulco it would persist for 28 and 52 h,respectively. Furthermore, at much greater distance, the air-port of Miami would suffer serious consequences from suchan eruptive scenario being disrupted for 21 h. The ash resi-dence time over other important international airports in theUnited States could be relatively high, including Atlanta(26 h) and Houston (38 h). Finally, the international airportof La Habana (Cuba) would suffer an ash residence time ofabout 25 h.

From the above it becomes clear that the hazardmaps presented here can be a useful tool for estimatingthe long-range hazard from a future Plinian eruption atPopocatépetl.

So far, the evaluation of volcanic ash hazards stemmingfrom other Mexican volcanoes have been carried out withmore simple semi-analytical models (Bonasia et al. 2011, inthe case of the Colima volcano) and by using the fully numer-ical model FALL3D (Bonasia et al. 2012, in the case of ElChichón volcano), but in both cases ash hazard maps existonly for ground loads at proximal to medial distances.

Here we present the first probabilistic long-range tephradispersal hazard assessment for a Mexican volcano with theprincipal aim of raising the public awareness with regard tothe huge potential impact that volcanic ash could have on thisregion in the future.

As shown, the impact would not be limited to areas withinthe boundaries of Mexico but also reach far beyond, includingimportant airports of international stature such as Miami,Atlanta, Dallas, and Houston, which together serve more than150million passengers per year. The importance of addressingthe problem of tephra dispersal hazards is underscored byavailable data on Plinian and sub-Plinian eruptions that haveoccurred in the entire region in the past 40,000 years (Fig. 1and Table 1). Although our data set is still quite fragmentary,these types of eruptions might be more frequent than previ-ously thought. Considering only the record for the past200 years (which should be fairly complete) yields a total offour eruptions (two per 100 years) for this short time period.Because the prevailing wind patterns and magnitudes of someof these eruptions were similar to those of the Popocatépetl“Ochre Pumice” eruption, the conclusions reached in thispaper serve as a starting point for future tephra dispersalhazard evaluation at neighboring strato-volcanoes.

This circumstance highlights the urgency of establishingand further strengthening international collaboration in thissector in order to effectively minimize the social and economicimpact of such eruptions.

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Acknowledgments The authors would like to thank CostanzaBonadonna, Marianne Guffanti, and an anonymous reviewer forconstructive reviews that helped improve the quality of the manuscript.

We also would like to thank Roberto Sulpizio for helpful discussion onstrategy and methodology. All numeric computations were performed atthe Computational Geodynamic Laboratory-CGEO (Centro deGeociencias, Campus Juriquilla, Querétaro, Universidad NacionalAutónoma de México) supercomputing facility—Horus. Work at Horuswas supported by project PAPIIT IN109613.

We thank Eurocontrol Network Management department for providingGIS air traffic data. Work at Popocatépetl and other Mexican volcanoescarried out by L. Arana-Salinas and C. Siebe has been supported by grantsCONACYT-167231 and UNAM-DGAPA-IN 1094.

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